VMAs function

VMA Model with Selected Lags

Performs the conditional maximum likelihood estimation of a VMA model with selected lags in the model

VMAs(da, malags, include.mean = T, fixed = NULL, prelim = F, details = F, thres = 2)

Arguments

• da: A T-by-k matrix of a k-dimensional time series with T observations
• malags: A vector consisting of non-zero MA lags
• include.mean: A logical switch to include the mean vector
• fixed: A logical matrix to fix coefficients to zero
• prelim: A logical switch concerning initial estimation
• details: A logical switch to control output level
• thres: A threshold value for setting coefficient estimates to zero

Details

A modified version of VMA model by allowing the user to select non-zero MA lags

Returns

• data: The observed time series

• MAlags: The VMA lags

• cnst: A logical switch to include the mean vector

• coef: The parameter estimates

• secoef: The standard errors of the estimates

• residuals: Residual series

• aic,bic: The information criteria of the fitted model

• Sigma: Residual covariance matrix

• Theta: The VMA matrix polynomial

• mu: The mean vector

• MAorder: The VMA order

References

Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Author(s)

Ruey S. Tsay

See Also

VMA